Management of Patients with Overactive Bladder in Brazil: A Retrospective Observational Study Using Data From the Brazilian Public Health System
Bibliographic record
Abstract
INTRODUCTION: In Brazil, current data on the use of healthcare resources to manage individuals with overactive bladder (OAB) are lacking. This study aimed to characterize contemporary treatment and the economic burden among patients with OAB managed under the Brazilian public health system (Sistema Único de Saúde [SUS]). METHODS: Population-based data from January to December of 2015 were acquired from Brazil's public health database. Adults at least 18 years of age with an ICD-10 diagnostic code for OAB within the period were included. Records of outpatient visits, hospitalizations, and onabotulinumtoxinA injections were used to calculate estimates of resource use and costs (in Brazilian reals [R$]) among those with OAB (frequency [%] and mean (standard deviation [SD]) as appropriate). Patient identifiers were not available, so a record linkage methodology was used to match medical encounters to individuals. Pharmacologic management of OAB was informed by government medication purchases available from the official Brazilian government databases. RESULTS: During 2015, 26,640 patients with OAB were identified. All cohort members had at least one outpatient visit and 15,349 (57.6%) were hospitalized. Of the study cohort, 10.0% visited a general practitioner (GP), 41.3% visited a specialist, and 52.0% visited other non-medical healthcare practitioners within the year. Mean (SD) healthcare costs among the study cohort totaled R$355 (R$866) per patient per year; and were R$291 (R$654), R$27 (R$130), R$27 (R$30), and R$11 (R$17) for hospitalizations, GP, specialist, and non-medical healthcare practitioner visits per patient per year, respectively. Regional analysis of reported government medication purchases suggested that access to OAB treatments is highly limited. CONCLUSIONS: High resource use and costs were estimated among patients with OAB managed within the SUS. These data provide a snapshot of the management of patients with OAB in Brazil, with the patients seeking treatment under SUS likely representing a more burdened subpopulation.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".